Get Labor Rate Benchmark

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool readOnly, openWorld, idempotent, and non-destructive, and the description adds meaningful behavioral detail beyond that: it explains the value_basis enum difference from get_price_benchmark, clarifies that next_year/second_year returns escalated out-year rates directly, and discloses that escalation is based on median year-over-year ceiling-rate growth rather than a guessed flat escalator.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence earns its place given the tool's 12 parameters and distinct output semantics. It is front-loaded with a one-sentence summary, then uses a scannable bullet list for parameters, and closes with the response shape. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the data source (GSA CALC), proposal use case, Pro-only access, all parameters, vendor lookup scenario, value-basis distinction from a sibling, and expected response fields including rate_distribution, escalation, category_breakdown, and rates_sample. With 12 parameters and no schema param descriptions, this is complete enough for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description fully compensates by explaining every parameter with examples and constraints (e.g. match 'contains' vs 'exact', education_level values, min/max_experience range, naics via SIN bridge, worksite values, business_size values, value_basis enums, sample_limit max 25). It adds meaning far beyond the raw schema titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: get an awarded labor-rate (should-cost) benchmark for a labor category from GSA CALC. It also clearly distinguishes itself from get_price_benchmark by framing the tool as the 'labor-cost input for a proposal' versus a 'contract-value read.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: 'Bid & Proposal / Negotiate tool, Pro only,' and explains when to use the vendor parameter for checking a competitor's or teammate's rate card. It references get_price_benchmark as the paired tool, which helps an agent choose between them, though it does not exhaustively discuss when not to use the tool relative to all wage-related siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.